The system disclosed herein is related generally to devices that are used in testing and identifying signals in a telecommunication line, and, particularly, to a hand-held spectrum analyzer used in testing and identifying signals such as Digital Subscriber Line (DSL) signals and their interferers.
Traditionally, scientists, engineers and trouble-shooting technicians have used test devices to identify the type of signals in a telecommunication line. Local loop analysis typically involves the detection of the types of signals in a customer""s line, and then detecting if any faults occur in the line. Identifying faults, interfering signals or stray frequencies present in a telecommunication line requires the detection of these faults, interfering signals or stray frequencies so as to allow a technician to take an appropriate action. Numerous devices are in the market to allow analysis of the local area network (LAN) or wide area network (WAN) protocols. The product TTC(trademark) FIREBERD marketed by Acterna Corporation of Germantown, Md. is an example of a device that can be used to analyze LAN/WAN signals.
The availability of miniaturization technologies such as the Personal Computer Memory Card International Association (PCMCIA) technologies makes it feasible to build portable test and analysis equipment to dynamically analyze telephony signals such as DSL signals using a hand-held computer. Further, though numerous devices are designed to identify and classify the type of signal in a local loop, no known device uses templates of known signal characteristics to match a known signal with an unknown signal, or to identify interfering or stray signals in a telecommunication line. Therefore, there is a need for an improvement in the art.
For purposes of this application, the word xe2x80x9cmatchxe2x80x9d (or any derivative of the word) should be understood as follows.
In a first definition, the word xe2x80x9cmatchxe2x80x9d is defined as follows: Where an unknown signal spectrum is correlated with several templates of known signal types, the unknown signal is said to have xe2x80x9cmatchedxe2x80x9d that known signal for which the correlation results in the largest (absolute) value.
In a second definition, the word xe2x80x9cmatchxe2x80x9d is defined as follows. If, upon correlating an unknown signal spectrum with a single known signal template, the absolute value of the correlation between the two signals is at or above a predetermined threshold level, then the two signals are deemed to match.
The correlation may be performed using the Cross Correlation Test, the Chi-Square Test, or the Kolmogorov-Smirnov Test, which are described in Donald Knuth, xe2x80x9cThe Art of Computer Programmingxe2x80x9d (Addison-Wesley, Pub., 1969). In alternative embodiments, any goodness-of-fit tests may be used to determine whether the signals are correlated.
In one aspect, the present disclosure is directed toward a hand-held spectrum analyzer. A hand-held computer, configured to fit in a person""s hand or a person""s shirt pocket, is programmed to perform signal processing and signal identification functions in one integrated unit. The hand-held spectrum analyzer may be configured to identify an unknown signal in a telecommunication line. The hand-held computer comprises, in one embodiment, an output device such as a flat-panel display screen or an audio output device.
In an embodiment of the disclosed method, a signal acquisition device captures signals from a telecommunication line such as a local loop. The captured signals are spectrally analyzed using a signal-processing unit. The output of the signal-processing unitxe2x80x94in the form of an unknown signal spectrumxe2x80x94is provided to a control unit comprising a signal identification system. This signal identification system could be a computer such as a programmed general-purpose computer.
A technician uses a device configured consistent with the principles disclosed herein to distinguish between the several types of signals and may then be able to determine if the signal pattern in the line matched a T-1 signal, an ADSL signal, an ISDN signal, or any other known signal whose template matches the unknown signal in accordance with a correlation function.
In another aspect, a method and apparatus consistent with the presently disclosed principles analyzes a telecommunication line such as a Plain Old Telephone System (POTS) line to identify unwanted or unknown signals that occur on the line. In case there is detected any unwanted or unknown signal, the disclosed system determines if any interfering signals are present in the telecommunication line. If interfering or unknown signals are present in the telecommunication line, a technician may identify such signals by matching the unknown signal with any known signal template(s). Alternatively, a technician may identify a stray frequency or interfering signal by visually determining the stray frequency or interfering signal according to an aspect of the disclosed method. This method includes the step of grouping frequencies that are adjacent to one another by a predetermined frequency points. If the interfering or unknown signal cannot be identified, the technician uses the device disclosed herein to isolate and quantify the stray frequency (if narrow band) or compares with stored signal templates for identification (if wideband). After the technician identifies the stray frequency or interfering signal, it can be stored temporarily or permanently in a storage device. The stored template could then be usedxe2x80x94during the matching stepxe2x80x94at a later time to determine if the unknown signal recurs at the same or at a different location.
Two stages of signal identification are possible. A first stage allows a technician to determine if the signal is a narrow band signal or a broadband signal by visually inspecting the result of a filtering function displayed on the hand-held computer flat-panel display screen, or audio output device.
In a second stage, the signal identification system comprises at least one of a plurality of spectra of known signals stored as templates. Using a matching algorithm, the spectrum of the test signal (unknown signal) is correlated with spectra of several known signals. The unknown signal is determined to be the same type as that of the known signal with whose spectrum the unknown signal produces the highest absolute correlation score. Algorithms such as Chi-Square Test, the Kolmogorov-Smirnov test, and the Cross Correlation test may be used to perform correlation operations.